Systems and methods for apportioning power consumption

ABSTRACT

The present disclosure includes a system and method for apportioning power consumption. In an example of apportioning power consumption according to the present disclosure, a transaction mix for a service is determined (104, 204, 330, 420), component resource usage for each of a number of components that are used while completing the service is determined (106, 206, 108, 208, 422), and component power consumption for each of the number of components is determined by use of the component resource usage (334, 424).

BACKGROUND

Energy efficiency is a concern in operating and managing computingservices. Energy consumption can affect the operational costs for thecomputing services and can contribute to the environmental impact ofcomputing services. Power-aware service management solutions requireaccess to power consumption data at the service level The powerconsumption of a computing service can be a useful tool in devisingmethods to improve energy efficiency for a computing service.

Deriving power consumption data for computing services can be achallenging task. Computing services, such as customer relationshipmanagement and electronic commerce services, can be complex and includemany service components running across multiple physical servers.Service components from different services can be co-located on a nodeand share resources on the node. In particular, virtual serverenvironments can include configurations where components and resourcesfor a computing service are shared among one or more physical servers.Therefore, directly measuring power consumption for a computing serviceat a service level can be difficult and many times can be impossible.

In some previous approaches, power models have be used to estimate powerconsumption. The power consumption estimates can use resource usage inthe power models, but these estimations can be difficult becauseresources can be shared by multiple computing services. Some previousapproaches have used physical system level power data to estimate powerconsumption, but these estimates can not be used to determine powerconsumption at the service level because physical system level powerdata does not include enough granularity to determine the individualservices that contribute the power consumption of the system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a computing operation relationship diagram illustratingbusiness computing services, transactions, components, and resourcesaccording to examples of the present disclosure.

FIG. 2 is a computing operation relationship diagram illustratingcomponents and resources in a computing transaction according toexamples of the present disclosure.

FIG. 3 is a method flow diagram illustrating apportioning powerconsumption of a number of components to a computing service accordingto examples of the present disclosure.

FIG. 4 is a block diagram illustrating determining power consumption ofa computing service 400 according to examples of the present disclosure.

FIG. 5 is a computing network system according to examples of thepresent disclosure.

DETAILED DESCRIPTION

The present disclosure includes a system and method for apportioningpower consumption. A method for apportioning power consumption caninclude determining a transaction mix for a service, determiningcomponent resource usage for each of a number of components that areused while completing the service, and determining component powerconsumption for each of the number of components by using the componentresource usage. The method can further include determining eachtransaction type in the service and the request rate for eachtransaction type, determining power impact factors for each of thenumber of components used in the service, and determining componentresource usage by summing the product of a component's resource demandfor each transaction type and the request rate for each transaction typeof the transaction mix for the service. Examples of the presentdisclosure can also include determining power consumption for theservice by aggregating component power consumption for each of thenumber of components.

In the following detailed description of the present disclosure,reference is made to the accompanying drawings that form a part hereof,and in which is shown by way of illustration how examples of thedisclosure may be practiced. These examples are described in sufficientdetail to enable those of ordinary skill in the art to practice thisdisclosure, and it is to be understood that other examples may beutilized and that process, electrical, and/or structural changes may bemade without departing from the scope of the present disclosure. As usedherein, the designators “N,” “M,” “P,”, “R,” “S,” “T,” “U,” and “V,”particularly with respect to reference numerals in the drawings,indicate that a number of the particular feature so designated can beincluded with examples of the present disclosure. The designators canrepresent the same or different numbers of the particular features.

The figures herein follow a numbering convention in which the firstdigit or digits correspond to the drawing figure number and theremaining digits identify an element or component in the drawing.Similar elements or components between different figures may beidentified by the use of similar digits. For example, 104 may referenceelement “04” in FIG. 1, and a similar element may be referenced as 204in FIG. 2. Elements shown in the various figures herein can be added,exchanged, and/or eliminated so as to provide a number of additionalexamples of the present disclosure. In addition, the proportion and therelative scale of the elements provided in the figures are intended toillustrate the examples of the present disclosure, and should not betaken in a limiting sense.

FIG. 1 is a computing operation relationship diagram illustratingcomputing services, transactions, components, and resources according toexamples of the present disclosure. In a computing network, servicessuch as logging data, browsing data, and requesting data, among otherservices, can be requested by a user. These services can be completed byexecuting a number of transactions using components, such servers, on acomputing network. A number of components can be included in a computingdevice that can have a number of resources. The component resources canbe portions of a component that provide for the functional operation ofthe component. The component resources consume power while executingtransactions. Component resources can include a number of processors, anumber of network interfaces, a number of input/output (IO) interfaces,hard disk operation, and memory operation, among other componentresources. The power consumed during a service by the components whilecompleting the service is a factor that can affect the cost of a serviceand is desirable to know. The following discussion will be made in thecontext of a computing service that uses servers and computing devicesto execute the service. However, examples of the present disclosure arenot limited to these examples, and the system and method of the presentdisclosure may be implemented in many other configurations, and appliedto many other services that use power consuming components.

in FIG. 1, computing operations can include a number of services 102-1,. . . , 102-N. The services 102-1, . . . , 102-N can include loggingdata, browsing data, and requesting data, among other services. Theservices 102-1, . . . 102-N can include a number of transactions 104-1,104-M, 104-P, . . . , 104-R. The transactions 104-1, 104-M, 104-P, . . .104-R can include operations that are performed by components on anetwork to execute a service 102-1, . . . 102-N. A service can includeany number of types of transactions and any number of each type oftransaction. The type of the transaction and the number of eachtransaction type and/or rate of each transaction type that make up aservice can be referred to as the transaction mix for a service.

In FIG. 1, the transaction mix for service 1 102-1 includes transaction1 104-1, transaction 2 104-2, and transaction M 104-M. The transactionmix for service 2 102-1 includes transaction 1 104-1, transaction 3104-3, and transaction P 104-P. The transaction mix for service N 102-Nincludes transaction 2 104-2, transaction 4 104-4, and transaction R104-R. Each of the transactions types, transaction 1 104-1, transaction2 104-2, transaction 3 104-3, transaction 4 104-4, transaction M 104-M,transaction P 104-P, and transaction R 104-R, for each of the services,service 1 104-1, service 2 102-2, and service N 104-N, include atransaction rate for the transaction type of a given service. Thetransaction mix, which includes the transaction rate for eachtransaction type of a service, for each service can be used to calculatethe component resource usage for the components used while completing aservice.

A service is completed by executing the transaction mix for the serviceon a number of components. The components can be servers on a network,such as a web server, an application server, a database server, and/or acomputer. In FIG. 1, a number of components, component 1 106-1,component 2 106-2, and component S 106-S, are illustrated. Each of thenumber of components include a number of resources, such as a processor,a network interface, an IO interface, hard disk operation, and memoryoperation, among other component resources. A component's resource canbe shared among a number of computing devices. In FIG. 1, component 1106-1 includes resource 1 108-1, resource 2 108-2, and resource T 108-T.The resources for component 2 106-1 include resource 1 108-1, resource 2108-2, and resource U 108-U. The resources for component S 106-S includeresource 1 108-1, resource 2 108-2, and resource V 108-V. Each componentcan include a number of resources that may or may not be used whileexecuting a transaction of a service. A service's resource usage is thesum of its transactions' resource usage. A service's power usage is thesum of its transactions' power usage. Transaction resource usage andpower usage cannot always be measured directly, but may be estimatedusing the method described below.

FIG. 2 is a computing operation relationship diagram illustratingcomponents and resources in a computing transaction according toexamples of the present disclosure. In FIG. 2, transaction M 204-Mincludes using component 1 206-1 and component 2 206-2 to executetransaction M 204-M. In some examples, component 1 206-1 could be a webserver, component 2 206-2 could be a database server, and transaction M204-M could be a data request for a browsing data service request from auser.

When transaction M 204-M is executed by component 1 206-1 and component2 206-2, a number of component resources are used. Component 1 206-1uses resource 1 208-1 and resource 2 208-2 and component 2 206-2 usesresource 2 208-2 and resource U 208-U. The rate at which the resourcesare used during execution of a transaction and the demand of eachresource can be used to determine the component resource usage for thecomponents that are used while executing a service. The componentresource usage for a service measures the amount that a componentresource is used during completion of a service.

FIG. 3 is a method flow diagram illustrating apportioning the powerconsumption of a number of component's resources to a computing serviceaccording to examples of the present disclosure. A computing service canuse a number of components that include a number of resources thatconsume power. FIG. 3 illustrates a method for apportioning the powerconsumption of the component's resources that were used in completingthe service to the service. In FIG. 3, apportioning power consumption300 includes determining a transaction mix for a service 330,determining component resource usage for each of a number of componentsthat are used while completing the service 332, determining componentpower consumption for each of the number of components by using thecomponent resource usage 334, and apportioning the component powerconsumption to the computing service based on the determined componentpower consumption for each of the plurality of components.

Apportioning the power consumption of a number of component's resourcesto a computing service can further include determining each transactiontype in the service and the request rate for each transaction type,determining power impact factors for each of the number of componentsused in the service, and determining component resource usage by summingthe product of a component's resource demand for each transaction typeand the request rate for each transaction type of the transaction mixfor the service. Examples of the present disclosure can also includedetermining power consumption for the service by aggregating componentpower consumption for each of the number of components.

FIG. 4 is a block diagram illustrating determining power consumption ofa computing service 400 according to examples of the present disclosure.In FIG. 4, determining power consumption of a computing service 400includes transaction metrics extraction 420. Transaction metricextraction 420 includes determining the transaction mix for a service.Transaction metrics for a service can include the types of transactionsthat are part of the service and the rate at which each transaction typeis requested and/or completed. As discussed above, the transaction mixincludes the type of the transactions (λ₁, λ₂, . . . , λ_(N)), where Nis the number of unique transaction types and λ₁ is the rate of eachtransaction type that make up a service. The transaction metrics can beextracted from monitoring data on a network. Transaction metrics for aservice can include the types of transactions that are part of theservice and the rate at which each transaction type is requested.

In examples of the present disclosure, if the transaction types for aservice are not given in the transaction metrics, a classifier can beconstructed to map the transactions based on the resource demand foreach transaction of a service. In examples the present disclosure, thetransaction metrics for the most popular transactions can be used tocreate the transaction mix. In some examples, the top 50 transactiontypes and rates may be used to create the transaction mix because theymay account for some portion, e.g., 98%, of the resource demand for acomponent when completing a service, which provides a significant sampleof the resource demand for a component allowing for a meaningfulcalculation of the component resource usage.

In FIG. 4, determining power consumption of a computing service 400includes service component resource usage calculation 422. The resourcedemands of different transaction types are usually different, but theresource demands of a single transaction type is relatively fixedirrespective of the transaction mix of the workload, since eachtransaction type usually has a relatively fixed code execution path. Theservice component resource usage calculation 422 uses the transactionmix that was created by the transaction metrics extraction 420. Thecomponent resource usage (U_(c)) for each component used during aservice is calculated by summing the product of the transaction rate foreach transaction type and the resource demand for each transaction type(α_(i)) and adding the background resource usage (U_(c,0)) to the sum.The background resource usage is the resource usage when there are notransactions being executed. The component resource usage (U_(c)) for acomponent c can be defined by the following equation:

$U_{c} = {{\sum\limits_{i = 1}^{N}{\alpha_{i} \cdot \lambda_{i}}} + U_{c,0}}$The resource demand for each transaction type (α_(i)) and the backgroundresource usage (U_(c,0)) can be calculated by linear regression from anumber of measurements of transaction mix and its corresponding measuredU_(c). The measurements may include the resource usage of the componentwhen no transactions are being executed.

In examples of the present disclosure, an aggregate resource usage modelfor a service can be created by summing the component resource usagecalculation for each component and adding the background load on thenode that each component is coupled to in a network.

The resource usage for each component used during a service may berelatively static across different transaction mixes and may beindependent of other service components on the same server. The resourceusage calculation for a component can be recalibrated based on measuredtransaction mix and estimates for α_(i) and U_(c,0) if there arenon-stationary changes to the workload on the component. Data can begathered for the changed transaction mix and resource demand operationsand used to periodically recalculate the component resource demand for aservice and background resource usage.

In examples of the present disclosure, a component resource usage can becalculated by adding the background resource usage (U_(c,0)) for acomponent to the product of an aggregate transaction rate for acomponent and an aggregate resource demand for a component. Thiscomponent resource usage calculation can be used when the transactionmix for a service is not known or when the transaction mix is relativelystationary for a service.

In FIG. 4, determining power consumption of a computing service 400includes service component power calculation 424. The service componentpower (P_(c)) calculation 424 uses the service component resource usage(U_(c)) calculation and power impact factors for each component. Powerimpact factors ρ, β, γ, and Θ for each component resource can becalculated by linear regression of data that includes power data foreach of the resources. Component resources can include a processor, anetwork input/output (IO) interface, hard disk operation, and memoryoperation, among other component resources. The service component powerconsumption (P_(c)) for each component used during a service can becalculated by summing the product of the component resource usage(U_(c)) and the power impact factor for each resource and adding thebackground power consumption (P_(b)) to the sum. The background powerconsumption (P_(b)) is the power consumption when none of the resourcesare being used to execute a transaction. The background powerconsumption can be calculated by linear regression of measurements ofthe power consumed by each resource when no transactions are beingexecuted. In examples of the present disclosure, the power impactfactors can be updated at periodic intervals by measuring the powerconsumption in real time. The service component power consumption(P_(c)) for each component used during a service can be can be definedby the following equation:P _(c) =P _(b) +ρ·U _(c1) +β·U _(c2) +γ·U _(c3) θ·U _(c4)where ρ, β, γ, and Θ are power impact factors for a processor, memory,disk IO, and network IO, respectively, and U_(c1), U_(c2), U_(c3), andU_(c4) are processor usage, memory usage, disk IO usage, and network IOusage, respectively. In some examples, the quantity of memory used maybe included in the baseline power consumption P_(b), In other examples,the quantity of memory used may be expressed as another term used tocompute P_(c).

In examples of the present disclosure, the processor resource is themajor power consumer for a component and using just the processor powerconsumption in the service component power calculation 424 provides anaccurate model of the power consumed by a component during a service. Inexamples of the present disclosure, a number of components can be on anode. Therefore, a node with a number of components can be used tocomplete a number of services, some even simultaneously. The backgroundpower consumption for the node, which includes a number of components,can be apportioned among the components that share the node. One methodto apportion the background power consumption is to assign the sameproportion of component resource usage to resource usage of the node tothe background power consumption for a component. Another method toapportion the background power consumption is to assign the backgroundpower consumption for a component as the component resource usagemultiplied by the background power consumption for the node and add thatto the product of the remaining, i.e., unaccounted for, background powerconsumption for the node multiplied by the ratio of the differencebetween peak and average resource usage for the component and the sum ofthe difference between peak and average resource usage for all thecomponents on the node. The peak resource usage is the 100-percentile ofresource usage for a component. in other examples, another percentile,such as the 95-percentile of resource usage could also be used in thesame manner.

in FIG. 4, apportioning power consumption includes service powercalculation 426. Service power calculation 426 includes summing theservice component power calculation 424 for each component of theservice. The service configuration can be used to determine thecomponents that are used in completing a service.

In examples of the present disclosure, the power consumption for servicecan be calculated by determining the transaction mix for a service,using the transaction mix to determine the component resource usage fora service, using the component resource usage for a service to determinethe component power consumption for a service, and summing powerconsumption for each component used in a service. The examples of thepresent disclosure can quantify the power consumption of a service whiletaking into account that services can have an impact on a componentspower consumption that is greater than just the power increase throughdirect resource demand of the service components used in a service.

Examples of the present disclosure can also provide a process model fora service that includes component resource usage models, component powerconsumption models, monitoring data, and service configuration data toobtain the service power consumption.

FIG. 5 is a computing network system 583 according to examples of thepresent disclosure. The computing network system 583 can include acommunication network 585 having a number of electronic devicescommunicatively coupled thereto. As shown in FIG. 5, communicationnetwork 585 can have a first mobile device 590, a first user device 587,a second user device 588, a first server 584-1, a second server 584-2,and a third server 584-3 communicatively coupled to network 585. Eachsystem component can be coupled to network 585 by a wired or wirelesscommunication channel. In FIG. 5, the first mobile device 590 is shownbeing coupled to the network 585 by a first communication channel 596;first user device 587 is shown being coupled to the network 585 by asecond communication channel 597; second user device 588 is shown beingcoupled to the network 585 by a third communication channel 598; firstserver 584-1 is shown being coupled to the network 585 by a fourthcommunication channel 599; second server 584-2 is shown being coupled tothe network 585 by a fifth communication channel 591; and third server584-3 is shown being coupled to the network 585 by a sixth communicationchannel 594.

Not all of the components and/or communication channels illustrated inFIG. 5 are required to practice the system and method of the presentdisclosure, and variations in the arrangement, type, and quantities ofthe components may be made without departing from the spirit or scope ofthe system and method of the present disclosure. Other computing networksystem components can include personal computers, laptop computers,mobile devices, cellular telephones, personal digital assistants, videogame consoles, or the like. Communication channels may be similar to, ordifferent from, other communication channels.

Generally, mobile device 590, and first and second user devices 587 and588, and first, second, and third servers 584-1, 584-2, and 584-3 mayinclude virtually any computing device capable of connecting to anothercomputing device to send and receive information, including web requestsfor information from a server device, and the like.

Mobile device 590 and the first and second user devices 587 and 588 mayfurther include a client application to manage various actions, forexample, a web browser application to enable an end-user to interactwith one or more servers (e.g., server 584) and/or other devices and/orapplications via network 585.

Servers 584-1, 584-2, and 584-3 may include a server application tomanage various actions, for example, a web-server application to enablean end-user to interact with servers 584-1, 584-2, and 584-3 via network585. In examples of the present disclosure, mobile device 590, first andsecond user devices 587 and 588, and servers 584-1, 584-2, and 584-3 maycomplete a computing service by executing the transactions that make upa service. In FIG. 5, first user device 587 includes a processor 592 anda non-transitory computer readable medium 593 for executinginstructions. Mobile device 590, first and second user devices 587 and588, and servers 584-1, 584-2, and 584-3 can include a number ofprocessors and non-transitory computer-readable media (e.g., memory)that store instructions executable by the number of processors. That is,the executable instructions can be stored in a fixed tangible mediumcommunicatively coupled to the one or more processors. Memory caninclude RAM, ROM, and/or mass storage devices, such as a hard diskdrive, tape drive, optical drive, solid state drive, and/or floppy diskdrive.

The non-transitory computer-readable media can be programmed withinstructions such as an operating system for controlling the operationof servers 584-1, 584-2, and 584-3, and/or computing services such aslogging data, browsing data, and requesting data, among other services.The operating system and/or applications may be implemented as one ormore executable instructions stored at one or more locations withinvolatile and/or non-volatile memory. Servers 584-1, 584-2, and 584-3 mayalso include an internal or external database, or other archive mediumfor storing, retrieving, organizing, and otherwise managing computingservices.

Mobile device 590 can also be a user device and include a processor incommunication with a non-transitory memory, a power supply, a number ofnetwork interfaces, an audio interface, a video interface, a display, akeyboard and/or keypad, and an optional global positioning systems (GPS)receiver. Mobile device 590 may optionally communicate with a basestation (not shown), or directly with another network component device.Network interfaces include circuitry for coupling the mobile device to anumber of networks, and is constructed for use with a number ofcommunication protocols and technologies including, but not limited to,e-mail, Internet, and/or wireless communication protocols. The networkinterface is sometimes known as a transceiver, transceiving device, ornetwork interface card (NIC).

Applications on client devices may include computer executableinstructions stored in a non-transient medium which, when executed by aprocessor, provide functions, such as a web browser, to enableinteraction with other computing devices such as a server, and/or thelike.

In some examples, the above discussed computing network system can beused, controlled, and/or the like through a web browser by a user. Insome examples, the web browser can communicate with a web server runningserver-side computing applications to perform computing services.

The above specification, examples and data provide a description of themethod and applications, and use of the system and method of the presentdisclosure. Since many examples can be made without departing from thespirit and scope of the system and method of the present disclosure,this specification merely sets forth some of the many possibleconfigurations and implementations.

Although specific examples have been illustrated and described herein,those of ordinary skill in the art will appreciate that an arrangementcalculated to achieve the same results can be substituted for thespecific examples shown. This disclosure is intended to coveradaptations or variations of a number of examples of the presentdisclosure. It is to be understood that the above description has beenmade in an illustrative fashion, and not a restrictive one. Combinationof the above examples, and other examples not specifically describedherein will be apparent to those of skill in the art upon reviewing theabove description. The scope of the number of examples of the presentdisclosure includes other applications in which the above structures andmethods are used. Therefore, the scope of number of examples of thepresent disclosure should be determined with reference to the appendedclaims, along with the full range of equivalents to which such claimsare entitled.

Various examples of the system and method for apportioning powerconsumption have been described in detail with reference to thedrawings, where like reference numerals represent like parts andassemblies throughout the several views. Reference to various examplesdoes not limit the scope of the system and method for displayingadvertisements, which is limited only by the scope of the claimsattached hereto. Additionally, any examples set forth in thisspecification are not intended to be limiting and merely set forth someof the many possible examples for the claimed system and method forapportioning power consumption.

Throughout the specification and claims, the meanings identified belowdo not necessarily limit the terms, but merely provide illustrativeexamples for the terms. The meaning of “a,” “an,” and “the” includesplural reference, and the meaning of “in” includes “in” and “on.” Thephrase “in an example,” as used herein does not necessarily refer to thesame example, although it may.

In the foregoing Detailed Description, some features are groupedtogether in a single example for the purpose of streamlining thedisclosure. This method of disclosure is not to be interpreted asreflecting an intention that the disclosed examples of the presentdisclosure have to use more features than are expressly recited in eachclaim. Rather, as the following claims reflect, inventive subject matterlies in less than all features of a single disclosed example. Thus, thefollowing claims are hereby incorporated into the Detailed Description,with each claim standing on its own as a separate example.

What is claimed:
 1. A method for apportioning power consumption, themethod implemented by a physical processor implementing machine readableinstructions, the method comprising: determining, by the processor, aplurality of transactions that are used to complete a computing service;determining, by the processor, a plurality of components that are usedto execute operations included in each transaction of the plurality oftransactions, wherein each component of the plurality of componentscomprises a plurality of resources that consume power while executingeach transaction of the plurality of transactions; determining, by theprocessor, a component resource usage for each component of theplurality of components based on resource demand by the plurality ofresources; determining, by the processor, a component power consumptionfor each component of the plurality of components based on the componentresource usage for each component of the plurality of components; andapportioning, by the processor, the component power consumption to thecomputing service based on the determined component power consumptionfor each component of the plurality of components.
 2. The method ofclaim 1, further comprising: determining, by the processor, atransaction mix for the computing service, wherein the transaction mixincludes a plurality of transaction types and a request rate at whicheach transaction type of the plurality of transactions types isrequested; and determining, by the physical processor, the componentresource usage for each component of plurality of components based onthe resource demand by the plurality of resources and the determinedtransaction mix.
 3. The method of claim 2, wherein each transaction ofthe plurality of transactions belongs to a particular transaction typeamong the plurality of transaction types in the transaction mix.
 4. Themethod of claim 3, wherein determining the component resource usage foreach component of the plurality of components includes determining, bythe processor, a product of a resource demand for each transaction typeof the plurality of transaction types and the request rate for eachtransaction type of the plurality of transaction types.
 5. The method ofclaim 1, wherein determining the component power consumption for eachcomponent of the plurality of components includes determining, by theprocessor, power impact factors for each component of the plurality ofcomponents.
 6. The method of claim 1, wherein determining the componentresource usage for each component of the plurality of componentsincludes determining, by the processor, background resource usage foreach component of the plurality of components, wherein the backgroundresource usage represents a resource usage when no transactions areexecuted.
 7. The method of claim 1, wherein determining the componentpower consumption for each component of the plurality of componentsincludes determining, by the processor, background power consumption foreach component of the plurality of components, wherein the backgroundpower consumption represents a power consumption when no transactionsare executed.
 8. The method of claim 1, wherein each resource of theplurality of resources represents a processor, a network interface, anI/O interface, a hard disk operation, or a memory operation.
 9. Themethod of claim 1, further comprising: constructing, by the physicalprocessor, a classifier that maps the plurality of transactions based ona resource demand for each transaction of the plurality of transactions.10. A non-transitory computer readable medium having machine readableinstructions stored thereon executable by a physical processor to:determine a plurality of transactions that are used to complete acomputing service; determining a plurality of components that are usedto execute operations included in each transaction of the plurality oftransactions, wherein each component of the plurality of componentsrepresents a virtual or physical computing device, and each component ofthe plurality of components comprises a plurality of resources thatconsume power while executing each transaction of the plurality oftransactions; determine component resource usage for each component ofthe plurality of components based on resource demand by the plurality ofresources; determine component power consumption for each component ofthe plurality of components by using the component resource usage; andapportion the component power consumption to the computing service basedon the determined power consumption for each component of the pluralityof components.
 11. The non-transitory computer readable medium of claim10, wherein the computing service includes a computing service oflogging data, browsing data, or adding data.
 12. The non-transitorycomputer readable medium of claim 10, wherein each component of theplurality of components includes one of a web server, an applicationserver, or a database server.
 13. The non-transitory computer readablemedium of claim 10, the non-transitory computer readable medium havingthe instructions stored thereon executable by the processor to:determine a transaction mix for the computing service, wherein thetransaction mix includes a plurality of transaction types in thecomputing service and a request rate for each transaction type of theplurality of transaction types; and determine the component resourceusage for each component of the plurality of components based on theresource demand by the plurality of resources and the determinedtransaction mix.
 14. The non-transitory computer readable medium ofclaim 13, the non-transitory computer readable medium having theinstructions stored thereon executable by the processor to: determine aresource demand of each transaction type of the plurality of transactiontypes based on a linear regression of data that includes the resourcedemand by the plurality of resources for each component of the pluralityof components.
 15. The non-transitory computer readable medium of claim14, the non-transitory computer readable medium having the instructionsstored thereon executable by the processor to: determine the componentresource usage for each component of the plurality of components bydetermining a sum of a product of the resource demand of eachtransaction type of the plurality of transaction types and the requestrate for each transaction type of plurality of transaction types. 16.The non-transitory computer readable medium of claim 10, thenon-transitory computer readable medium having the instructions storedthereon executable by the processor to: determine the component powerconsumption for each component of the plurality of components includesdetermining power impact factors for each component of the plurality ofcomponents.
 17. A power consumption apportioning system, comprising: aplurality of communicatively coupled user computing devices; and atleast one server computing device communicatively coupled to theplurality of communicatively coupled user computing devices, the servercomputing device comprising: at least one physical processor; anon-transitory memory in communication with the at least one physicalprocessor, the non-transitory memory being programmed with instructionsexecutable on the at least one physical processor to: determine atransaction mix that comprises a plurality of transaction types for acomputing service and a request rate at which each transaction type ofthe plurality of transaction types is requested; determine a pluralityof transactions that are used to complete the computing service;determine a plurality of components that are used to execute operationsincluded in each of the plurality of transactions, wherein eachcomponent of the plurality of components comprises a plurality ofresources that consume power while executing each transaction of theplurality of transactions; determine component resource usage for eachcomponent of the plurality of components based on at least one of: (i)the request rate for each transaction type of the plurality oftransaction types, and (ii) resource demand that is made by theplurality of resources to execute each transaction of the plurality oftransactions, wherein each transaction of the plurality of transactionscorresponds to a particular transaction type among the plurality oftransaction types; determine component power consumption for eachcomponent of the plurality of components by using the component resourceusage; and apportion the component power consumption to the computingservice based on the determined component power consumption for eachcomponent of the plurality of components.
 18. The power consumptionapportioning system of claim 17, wherein the non-transitory memory isprogrammed with instructions executable on at least one physical theprocessor to: determine the transaction mix for the computing service,wherein the transaction mix includes the plurality of transaction typesand a request rate at which each transaction type of the plurality oftransactions types is requested; and determine the component resourceusage for each component of plurality of components based on theresource demand by the plurality of resources and the determinedtransaction mix.
 19. The power consumption apportioning system of claim17, wherein determining the component power consumption for eachcomponent of the plurality of components includes determining powerimpact factors for each component of the plurality of components.